Retrospective self-reports play a central role in basic and applied research on drug use. The proposed study introduces and tests a fuzzy-set model to improve retrospective self-reports of the frequeny, onset, ad amount of drug use (i.e., tobacco, alcohol, marijuana). Different from traditional modelsof self-reported data, this fuzzy set model assumes that self-reprots of high-frequency behaviors cannot be properly represented by a single point estimate. Instead, self-reports ae better measured, interpreted, and analyzed as membership distributions of possible, partially valid estimates. Six-hundred aldult residents of the San Diego metropolitan area will be recruited to participate in three distinct experiments to probe the validity of this model. Experiment 1 is designed to quantify and distinguish fuzziness in self-reports from other sources of error and uncertainty. Experiment 2 compares the susceptibility of traditional point and fuzzy set estimates to socilly desirable response sets. Finally, Experiment 3 is designed to compare the criterion-related validity of traditional point estimates and fuzzy estimates of health and social behaviros in different gender and ethnic groups. In summary, this study investigates an innovative approach to representing self-reports to questions regarding the frequency, duration, or amount of drug use. The proposed study builds on our previous research and advances the state-of-the-art by combining cognitive models of retrospective self-report and psychometric theory. The proposed fuzzy-set model promises to yield measures of behaviors that more completely reflect what can be recalled about past drug use, it provides a framework for studying bias, precision, and uncertainty of self-reprots. Findings from this study could have significant implications for improving the collection, analysis, and interpretation of self-reports in large-scale national surveys (e.g., national helath Interview Survey, national Householf Survey of Drug Abuse), in epidemiologic and behaviroal research, and in everyday life.